Messaging campaigns in today's “always on, always connected” world are ubiquitous. To support such campaigns, marketers and advertisers demand fast and reliable access to a vast and diverse array of anonymous user data captured from multiple channels, devices and touchpoints. Specifically, for example, with the proliferation of mobile devices (e.g., smartphones, tablets, etc.), the average person now owns multiple devices (e.g., averaging upwards of three in the US, according to some surveys) and is using these devices at different times of the day for various mobile activities (e.g., work, email, web browsing, online shopping, watching TV, watching movies, etc.). These same device users can also have one or more devices at home (e.g., laptop computer, desktop computer, internet TV, etc.) that they further use for additional online activities. Various techniques have been developed to record the user activity (e.g., search terms, clicks, device IDs, etc.) in the mobile and online environments. In addition, users can perform various offline activities that can be recorded using more traditional means (e.g., customer relationship management or CRM systems, point of sale or POS systems, etc.).
To improve the effectiveness (e.g., reach, conversion rate, optimized media spend, etc.) of messaging campaigns (e.g., online advertising campaigns, etc.), advertisers attempt to gain exposure to each potential customer in as many settings as possible. For example, advertisers may be able to reach a customer based on a stored cookie regardless of whether the user is using Internet Explorer or FireFox. Privacy laws or privacy expectations may prevent advertisers from getting too much information about each user beyond each advertiser's direct interactions with the user. Techniques are needed to reach larger target audiences in a messaging campaign, regardless of the particular device that an audience member might be using, regardless of the source of information (possibly from different potential advertisers) that would make a particular audience member a good target for the marketing message, and without violating the privacy laws or privacy expectations of any individuals.
Legacy approaches to identifying a user from data received from multiple sources or settings (e.g., home and office settings) have limitations. What is needed is a technique or techniques to more broadly identify users who might benefit from the messaging of a marketing campaign.